{"id":"https://openalex.org/W3139091945","doi":"https://doi.org/10.1109/tim.2021.3068433","title":"RFID Dynamic Performance Measurement System Embedded in Multiscale Deep Learning","display_name":"RFID Dynamic Performance Measurement System Embedded in Multiscale Deep Learning","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3139091945","doi":"https://doi.org/10.1109/tim.2021.3068433","mag":"3139091945"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2021.3068433","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2021.3068433","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100412878","display_name":"Lin Li","orcid":"https://orcid.org/0000-0002-4364-301X"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lin Li","raw_affiliation_strings":["College of Science, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"College of Science, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101804472","display_name":"Xiaolei Yu","orcid":"https://orcid.org/0000-0003-4859-6352"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiaolei Yu","raw_affiliation_strings":["National Quality Supervision and Testing Center for RFID Product (Jiangsu), Nanjing, China"],"affiliations":[{"raw_affiliation_string":"National Quality Supervision and Testing Center for RFID Product (Jiangsu), Nanjing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046394019","display_name":"Zhenlu Liu","orcid":"https://orcid.org/0000-0003-4012-385X"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenlu Liu","raw_affiliation_strings":["College of Science, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"College of Science, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062880214","display_name":"Zhimin Zhao","orcid":"https://orcid.org/0000-0001-6148-1168"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhimin Zhao","raw_affiliation_strings":["College of Science, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"College of Science, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100365744","display_name":"Ke Zhang","orcid":"https://orcid.org/0000-0002-9289-4122"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ke Zhang","raw_affiliation_strings":["College of Science, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"College of Science, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031787964","display_name":"Shanhao Zhou","orcid":"https://orcid.org/0000-0002-3066-0646"},"institutions":[{"id":"https://openalex.org/I9842412","display_name":"Nanjing University of Aeronautics and Astronautics","ror":"https://ror.org/01scyh794","country_code":"CN","type":"education","lineage":["https://openalex.org/I9842412"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shanhao Zhou","raw_affiliation_strings":["College of Science, Nanjing University of Aeronautics and Astronautics, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"College of Science, Nanjing University of Aeronautics and Astronautics, Nanjing, China","institution_ids":["https://openalex.org/I9842412"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100412878"],"corresponding_institution_ids":["https://openalex.org/I9842412"],"apc_list":null,"apc_paid":null,"fwci":0.3015,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.62629838,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"70","issue":null,"first_page":"1","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection Techniques","score":0.9969000220298767,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/deblurring","display_name":"Deblurring","score":0.767920970916748},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7219838500022888},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6854649782180786},{"id":"https://openalex.org/keywords/reading","display_name":"Reading (process)","score":0.6002839803695679},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5826343297958374},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5359251499176025},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.534997820854187},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5122544169425964},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42328783869743347},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.41203010082244873},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3537403345108032},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.29557472467422485},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2341647446155548},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.2080521285533905},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14664381742477417},{"id":"https://openalex.org/keywords/image-restoration","display_name":"Image restoration","score":0.13629060983657837}],"concepts":[{"id":"https://openalex.org/C2777693668","wikidata":"https://www.wikidata.org/wiki/Q25053743","display_name":"Deblurring","level":5,"score":0.767920970916748},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7219838500022888},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6854649782180786},{"id":"https://openalex.org/C554936623","wikidata":"https://www.wikidata.org/wiki/Q199657","display_name":"Reading (process)","level":2,"score":0.6002839803695679},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5826343297958374},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5359251499176025},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.534997820854187},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5122544169425964},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42328783869743347},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.41203010082244873},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3537403345108032},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.29557472467422485},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2341647446155548},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.2080521285533905},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14664381742477417},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.13629060983657837},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2021.3068433","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2021.3068433","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.8700000047683716}],"awards":[{"id":"https://openalex.org/G1690348453","display_name":null,"funder_award_id":"XYDXX-058","funder_id":"https://openalex.org/F4320326182","funder_display_name":"Six Talent Peaks Project in Jiangsu Province"},{"id":"https://openalex.org/G4473325952","display_name":null,"funder_award_id":"61771240","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320326182","display_name":"Six Talent Peaks Project in Jiangsu Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W1533861849","https://openalex.org/W1974675259","https://openalex.org/W1982788633","https://openalex.org/W1993357945","https://openalex.org/W1993748636","https://openalex.org/W2011181254","https://openalex.org/W2049751289","https://openalex.org/W2062903423","https://openalex.org/W2084946427","https://openalex.org/W2104904368","https://openalex.org/W2284140358","https://openalex.org/W2297585722","https://openalex.org/W2321571768","https://openalex.org/W2395360537","https://openalex.org/W2481600904","https://openalex.org/W2527433359","https://openalex.org/W2560533888","https://openalex.org/W2565639579","https://openalex.org/W2570343428","https://openalex.org/W2591722035","https://openalex.org/W2770342399","https://openalex.org/W2773366896","https://openalex.org/W2791021610","https://openalex.org/W2796347433","https://openalex.org/W2796908152","https://openalex.org/W2803848973","https://openalex.org/W2808969558","https://openalex.org/W2899372083","https://openalex.org/W2901565115","https://openalex.org/W2903331227","https://openalex.org/W2905909895","https://openalex.org/W2920770442","https://openalex.org/W2949730495","https://openalex.org/W2963037989","https://openalex.org/W2963130865","https://openalex.org/W2970667381","https://openalex.org/W2972309292","https://openalex.org/W2982041717","https://openalex.org/W2982945348","https://openalex.org/W2986101901","https://openalex.org/W2992850863","https://openalex.org/W3022640110","https://openalex.org/W3028223633","https://openalex.org/W3105070560","https://openalex.org/W4293584584","https://openalex.org/W6631943919","https://openalex.org/W6750227808","https://openalex.org/W6763449883","https://openalex.org/W6966737060"],"related_works":["https://openalex.org/W3200192952","https://openalex.org/W2062923025","https://openalex.org/W4308216825","https://openalex.org/W4312281738","https://openalex.org/W4226493464","https://openalex.org/W4312417841","https://openalex.org/W3193565141","https://openalex.org/W3133861977","https://openalex.org/W3167935049","https://openalex.org/W3029198973"],"abstract_inverted_index":{"Multitag":[0],"sensitivity":[1,20],"would":[2],"be":[3],"affected":[4],"by":[5,48,91,111,130],"electromagnetic":[6],"coupling":[7],"during":[8],"simultaneous":[9],"reading.":[10],"The":[11,34,153],"reading":[12,32,44,54,159,181],"distance":[13,55,182],"of":[14,24,31,37,46,56,100,117,127,161,173,183,193],"multitag":[15,47,57,65,184],"depends":[16],"on":[17,69],"the":[18,43,53,60,85,97,114,137,142,149,158,162,171,180,186,190,194],"least":[19],"and":[21,79,104,189],"operating":[22],"power":[23],"all":[25],"tags,":[26],"which":[27],"is":[28,40,109],"an":[29],"indicator":[30],"performance.":[33],"main":[35],"purpose":[36],"this":[38],"article":[39],"to":[41],"optimize":[42],"performance":[45,160],"embedding":[49],"deep":[50],"learning,":[51],"while":[52],"changes":[58],"with":[59,136],"3-D":[61,115,125,143],"geometric":[62],"structure.":[63],"Dynamic":[64],"image":[66,76,87],"deblurring":[67],"based":[68],"multiscale":[70],"convolutional":[71],"neural":[72],"network":[73],"(MCNN)":[74],"improves":[75],"restoration":[77],"ability":[78,99,192],"clarity.":[80],"Also,":[81],"tag":[82],"detection":[83,98],"from":[84,185],"estimated":[86],"via":[88],"YOLOv3":[89],"improved":[90,169],"feature":[92],"enhancement":[93],"(YOLOv3_f)":[94],"can":[95,178],"improve":[96,179],"small":[101],"size":[102],"targets,":[103],"mean":[105],"average":[106],"precision":[107],"(mAP)":[108],"increased":[110],"16.4%.":[112],"Finally,":[113],"coordinates":[116,126],"tags":[118,174],"in":[119,148],"pixel":[120],"space":[121,129],"are":[122,146],"converted":[123],"into":[124],"world":[128],"a":[131],"quaternion.":[132],"Comparing":[133],"our":[134],"system":[135,165],"positioning":[138],"method":[139],"without":[140],"deblurring,":[141],"coordinate":[144],"structures":[145],"tested":[147],"dynamic":[150],"measurement":[151],"system.":[152,196],"experimental":[154],"results":[155],"show":[156],"that":[157],"designed":[163],"RFID":[164,195],"has":[166],"been":[167],"greatly":[168],"as":[170],"number":[172],"increases.":[175],"Our":[176],"scheme":[177],"physical":[187],"structure":[188],"anticollision":[191]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}